{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 坐标轴坐标网样式化\n",
    "fig, axes = plt.subplots(1,3, figsize = (12,4))\n",
    "x = np.arange(-100,100)\n",
    "axes[0].plot(x, x**3)\n",
    "axes[0].grid(True)\n",
    "axes[0].set_title('default grid')\n",
    "axes[0].set_xlabel(\"x axis\")\n",
    "axes[0].set_ylabel(\"y axis\")\n",
    "\n",
    "axes[1].plot(x, x**2,\"r\")\n",
    "axes[1].grid(color=\"r\",ls=\"-\",lw=1)\n",
    "axes[1].set_title(\"custom grid\")\n",
    "axes[1].spines['left'].set_color('red')\n",
    "axes[1].spines['bottom'].set_color('blue')\n",
    "\n",
    "axes[2].plot(x,x,\"y\")\n",
    "axes[2].set_title(\"no grid\")\n",
    "axes[2].spines['right'].set_color(None)\n",
    "axes[2].spines['top'].set_color(None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 设置坐标轴的取值范围\n",
    "fig = plt.figure()\n",
    "a1 = fig.add_axes([0,0,1,1])\n",
    "import numpy as np\n",
    "x = np.arange(1,10)\n",
    "a1.plot(x, np.exp(x),'r')\n",
    "a1.set_title('exp')\n",
    "#设置y轴\n",
    "a1.set_ylim(0,10000)\n",
    "#设置x轴\n",
    "a1.set_xlim(0,10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 设置坐标轴的刻度和标签\n",
    "import math\n",
    "x = np.arange(0, math.pi*2, 0.05)\n",
    "#生成画布对象\n",
    "fig = plt.figure()\n",
    "#添加绘图区域\n",
    "ax = fig.add_axes([0, 0, 1, 1])\n",
    "y = np.sin(x)\n",
    "ax.plot(x, y)\n",
    "#设置x轴标签\n",
    "ax.set_xlabel('angle')\n",
    "ax.set_title('sine')\n",
    "ax.set_xticks([0,2,4,6,8])\n",
    "#设置x轴刻度标签\n",
    "ax.set_xticklabels(['zero','two','four','six','eight'])\n",
    "#设置y轴刻度\n",
    "ax.set_yticks([-1,0,1])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
